Charging station collaborative optimization control method based on double-center Q learning

Abstract

The invention discloses a charging station collaborative optimization control method based on double-center Q learning. The method comprises the following steps of: 1, describing a control process ofelectric vehicle charging service requests of two randomly arrived charging forms as an event-driven decision process, 2, describing a control process of responding to the peak-load regulation electricity price plan of the power grid by the electric vehicle which is being charged in the charging station as a sequential decision process, 3, taking the peak-load regulation electricity price and theonline service state of the charging pile as system states, 3, taking the service request proposed by the arrival electric vehicle as an event, and selecting whether to access and provide a charging service as an access control action, 4, at the peak-load regulation electricity price issuing moment, selecting the charging and discharging actions of all the alternating-current charging electric vehicles serving as peak-load regulation control actions, and 5, performing online collaborative optimization on the electric vehicle access control center and the peak-load regulation response control center of the system by adopting a Q learning algorithm. Effective electric vehicle intelligent access control and peak-load regulation response control can be performed on the charging station so as to adapt to the power grid peak-load regulation requirement.

Description

technical field [0001] The invention belongs to the technical field of intelligent control and optimization, and specifically relates to a dual-center Q-learning-based collaborative optimization control method for charging stations. Background technique [0002] my country is currently the largest automobile consumer market in the world. Automobile manufacturers have shifted the focus of R&D and production from traditional energy-powered vehicles to new energy vehicles. Among them, electric vehicles will be the development of new energy vehicles for a long period of time. Mainstream, with huge consumption potential, the market share will also increase. The charging pile is an important infrastructure for providing charging services for electric vehicles, and it is also an important link in the process of industrialization and commercialization of electric vehicles. With the rapid development of the electric vehicle industry and the substantial increase in the number of elect...

AI Technical Summary

Problems solved by technology

[0003] The existing grid electricity price adopts a very simple and fixed time-of-use electricity price mechanism. It does not dynamically formulate or adjust the grid peak-shaving electricity price plan according to the actual forecast of the grid's source load, and the charging station service system does not follow the actual grid peak load regulation. The electricity price plan dynamically and adaptively performs adaptive access control on the charging request of electric vehicles, and performs adaptive peak-shaving response control on the charging and discharging actions of electric vehicles

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